Effect of Postoperative Radiation Therapy Timing on Survival in Pediatric and Young Adult Ependymoma

Purpose Postoperative radiation therapy (RT) is commonly used for World Health Organization grade II-III intracranial ependymoma. Clinicians generally aim to begin RT ≤5 weeks after surgery, but postoperative recovery and need for second look surgery can delay the initiation of adjuvant therapy. On ACNS 0831, patients were required to enroll ≤8 weeks after initial surgery and begin adjuvant therapy within 3 weeks after enrollment. The purpose of this study was to determine the optimal timing of RT after surgery. Methods and Materials The National Cancer Database was queried for patients (aged 1-39 years) with localized World Health Organization grade II-III intracranial ependymoma treated with surgery and postoperative RT. Overall survival (OS) curves were plotted based on RT timing (≤5 weeks, 5-8 weeks, and \u3e8 weeks after surgery) and were compared by log-rank test. Factors associated with OS were identified by multivariate analysis. After 2009, complete data were available on whether patients underwent gross total resection or subtotal resection. Planned subset analysis was performed to examine the effect of RT timing on OS in patients with known extent of resection. Results In the final analytical data set of 1043 patients, no difference in 3-year OS was observed in patients who initiated RT ≤5 weeks, 5 to 8 weeks, and \u3e8 weeks after surgery (89.8% vs 89.1% vs 88.4%; P = .796). On multivariate analysis, grade III tumors (hazard ratio, 2.752; 95% confidence interval, 1.969-3.846, P \u3c .001) and subtotal resection (hazard ratio, 2.253; 95% confidence interval, 1.405-3.611, P \u3c .001) were significantly associated with reduced OS. Timing of RT, total RT dose, age, and other factors were not significant. These findings were affirmed in the subset of patients treated between 2010 and 2016, when extent of resection was routinely recorded. Conclusions Delayed postoperative RT was not associated with inferior survival in patients with intracranial ependymoma. Delayed RT initiation may be acceptable in patients who require longer postoperative recovery or referral to an appropriate RT center, but should be minimized whenever practical

Ablative 5-fraction stereotactic magnetic resonance-guided radiation therapy (MRgRT) with on-table adaptive replanning and elective nodal irradiation for inoperable pancreas cancer

Purpose: Radiotherapy (RT) dose escalation using stereotactic body radiation therapy (SBRT) may significantly improve both local control (LC) and overall survival (OS) for patients with inoperable pancreas cancer. However, ablative dose cannot be routinely offered because of the risk of causing severe injury to adjacent normal organs. Stereotactic magnetic resonance (MR)-guided adaptive radiation therapy (SMART) represents a novel technique that may achieve safe delivery of ablative dose and improve long-term outcomes. Methods and materials: We performed a single institution retrospective analysis of 35 consecutive pancreatic cancer patients treated with SMART in mid-inspiration breath hold on an MR-LINAC. Most had locally advanced disease (80%) and received induction chemotherapy (91.4%) for a median 3.9 months prior to SBRT. All were prescribed 5 fractions delivered in consecutive days to a median total dose of 50 Gy (BED10 100 Gy10), typically with a 120-130% hotspot. Elective nodal irradiation was delivered to 20 (57.1%) patients. No patient had fiducial markers placed and all were treated with continuous intrafraction MR visualization and automatic beam triggering. Results: With median follow-up of 10.3 months from SMART, acute (2.9%) and late (2.9%) grade 3 toxicities were uncommon. One-year LC, distant metastasis-free survival, progression-free survival, cause-specific survival, and OS were 87.8%, 63.1%, 52.4%, 77.6% and 58.9%, respectively. Conclusions: To our knowledge, this is the first report of 5-fraction pancreas SMART delivered on an MR-LINAC. We observed minimal severe treatment-related toxicity and encouraging early LC. Prospective confirmation of feasibility and long-term clinical outcomes of dose intensified SMART is warranted

Systematic review and meta-analysis of lung cancer brain metastasis and primary tumor receptor expression discordance

Background: Treatment paradigms for metastatic non-small cell lung cancer are increasingly based on biomarker-driven therapies, with the most common alteration being mutation in the epidermal growth factor receptor (EGFR). Change in expression of such biomarkers could have a profound impact on the choice and efficacy of a selected targeted therapeutic, and hence the objective of this study was to analyze discordance in EGFR status in patients with lung cancer brain metastasis (LCBM). Methods: Using PRISMA guidelines, a systematic review was performed of series in the Medline database of biopsied or resected LCBM published before May, 2020. Key words included “lung cancer” and “brain metastasis” combined with “epidermal growth factor receptor/EGFR,” and “receptor conversion/discordance or concordance.” Weighted random effects models were used to calculate pooled estimates. Results: We identified 501 patients from 19 full-text articles for inclusion in this study. All patients underwent biopsy or resection of at least one intracranial lesion to compare to the primary tumor. On primary/LCBM comparison, the weighted pooled estimate for overall EGFR receptor discordance was 10% (95% CI 5–17%). The weighted effects model estimated a gain of an EGFR mutation in a brain metastases in patients with negative primary tumors was 7% (95% CI 4–12%). Alternatively, the weighted effects model estimate of loss of an EGFR mutation in patients with detected mutations in the primary tumor was also 7% (95% CI 4–10%). KRAS testing was also performed on both primary tumors and LCBM in a subset of 148 patients. The weighted effects estimate of KRAS-mutation discordance among LCBM compared to primary tumors was 13% (95% CI 5–27%). The weighted effects estimated of KRAS gain and loss in LCBM was 10% (95% CI 6–18%) and 8% (95% CI 4–15%), respectively. Meta-regression analysis did not find any association with any factors that could be associated with discordances. Conclusions: EGFR and KRAS mutation status discordance between primary tumor and LCBM occurs in approximately 10% and 13% of patients, respectively. Evaluation of LCBM receptor status is key to biomarker-driven targeted therapy for intracranial disease and awareness of subtype switching is critical for those patients treated with systemic therapy alone for intracranial disease

Hospitalization rates from radiotherapy complications in the United States

Hospitalizations due to radiotherapy (RT) complications result in significant healthcare expenditures and adversely affect the quality of life of cancer patients. Using a nationally representative dataset, the objective of this study is to identify trends in the incidence of these hospitalizations, their causes, and the resulting financial burden. Data from the National Inpatient Sample was retrospectively analyzed from 2005 to 2016. RT complications were identified using ICD-9 and ICD-10 external cause-of-injury codes. The hospitalization rate was the primary endpoint, with cost and in-hospital death as secondary outcomes. 443,222,223 weighted hospitalizations occurred during the study period, of which 482,525 (0.11%) were attributed to RT. The 3 most common reasons for RT-related hospitalization were cystitis (4.8%, standard error [SE] = 0.09), gastroenteritis/colitis (3.7%, SE = 0.07), and esophagitis (3.5%, SE = 0.07). Aspiration pneumonitis (1.4-fold) and mucositis (1.3-fold) had the highest relative increases among these hospitalizations from 2005 to 2016, while esophagitis (0.58-fold) and disorders of the rectum and anus were the lowest (0.67-fold). The median length of stay of patient for hospitalization for RT complications was 4.1 (IQR, 2.2–7.5) days and the median charge per patient was $10,097 (IQR, 5755–18,891) and the total cost during the study period was$4.9 billion. Hospitalization for RT-related complications is relatively rare, but those that are admitted incur a substantial cost. Use of advanced RT techniques should be employed whenever possible to mitigate the risk of severe toxicity and therefore reduce the need to admit patients

Hospitalization rates for complications due to systemic therapy in the United States

The aim of this study was to estimate the trends and burdens associated with systemic therapy-related hospitalizations, using nationally representative data. National Inpatient Sample data from 2005 to 2016 was used to identify systemic therapy-related complications using ICD-9 and ICD-10 external causes-of-injury codes. The primary outcome was hospitalization rates, while secondary outcomes were cost and in-hospital mortality. Overall, there were 443,222,223 hospitalizations during the study period, of which 2,419,722 were due to complications of systemic therapy. The average annual percentage change of these hospitalizations was 8.1%, compared to − 0.5% for general hospitalizations. The three most common causes for hospitalization were anemia (12.8%), neutropenia (10.8%), and sepsis (7.8%). Hospitalization rates had the highest relative increases for sepsis (1.9-fold) and acute kidney injury (1.6-fold), and the highest relative decrease for dehydration (0.21-fold) and fever of unknown origin (0.35-fold). Complications with the highest total charges were anemia ($4.6 billion), neutropenia ($3.0 billion), and sepsis ($2.5 billion). The leading causes of in-hospital mortality associated with systemic therapy were sepsis (15.8%), pneumonia (7.6%), and acute kidney injury (7.0%). Promoting initiatives such as rule OP-35, improving access to and providing coordinated care, developing systems leading to early identification and management of symptoms, and expanding urgent care access, can decrease these hospitalizations and the burden they carry on the healthcare system

Factors associated with unplanned readmissions and costs following resection of brain metastases in the United States

The purpose of this study was to critically analyze the risk of unplanned readmission following resection of brain metastasis and to identify key risk factors to allow for early intervention strategies in high-risk patients. We analyzed data from the Nationwide Readmissions Database (NRD) from 2010–2014, and included patients who underwent craniotomy for brain metastasis, identified using ICD-9-CM diagnosis (198.3) and procedure (01.59) codes. The primary outcome of the study was unplanned 30-day all-cause readmission rate. Secondary outcomes included reasons and costs of readmissions. Hierarchical logistic regression model was used to identify the factors associated with 30-day readmission following craniotomy for brain metastasis. During the study period, 44,846 index hospitalizations occurred for patients who underwent resection of brain metastasis. In this cohort, 17.8% (n = 7,965) had unplanned readmissions within the first 30 days after discharge from the index hospitalization. The readmission rate did not change significantly during the five-year study period (p-trend = 0.286). The median per-patient cost for 30-day unplanned readmission was $11,109 and this amounted to a total of$26.4 million per year, which extrapolates to a national expenditure of $269.6 million. Increasing age, male sex, insurance status, Elixhauser comorbidity index, length of stay, teaching status of the hospital, neurological complications and infectious complications were associated with 30-day readmission following discharge after an index admission for craniotomy for brain metastasis. Unplanned readmission rates after resection of brain metastasis remain high and involve substantial healthcare expenditures. Developing tools and interventions to prevent avoidable readmissions could focus on the high-risk patients as a future strategy to decrease substantial healthcare expense

Hospitalization rates for complications due to systemic therapy in the United States

The aim of this study was to estimate the trends and burdens associated with systemic therapy-related hospitalizations, using nationally representative data. National Inpatient Sample data from 2005 to 2016 was used to identify systemic therapy-related complications using ICD-9 and ICD-10 external causes-of-injury codes. The primary outcome was hospitalization rates, while secondary outcomes were cost and in-hospital mortality. Overall, there were 443,222,223 hospitalizations during the study period, of which 2,419,722 were due to complications of systemic therapy. The average annual percentage change of these hospitalizations was 8.1%, compared to − 0.5% for general hospitalizations. The three most common causes for hospitalization were anemia (12.8%), neutropenia (10.8%), and sepsis (7.8%). Hospitalization rates had the highest relative increases for sepsis (1.9-fold) and acute kidney injury (1.6-fold), and the highest relative decrease for dehydration (0.21-fold) and fever of unknown origin (0.35-fold). Complications with the highest total charges were anemia ($4.6 billion), neutropenia ($3.0 billion), and sepsis ($2.5 billion). The leading causes of in-hospital mortality associated with systemic therapy were sepsis (15.8%), pneumonia (7.6%), and acute kidney injury (7.0%). Promoting initiatives such as rule OP-35, improving access to and providing coordinated care, developing systems leading to early identification and management of symptoms, and expanding urgent care access, can decrease these hospitalizations and the burden they carry on the healthcare system

Hospitalization rates for complications due to systemic therapy in the United States

The aim of this study was to estimate the trends and burdens associated with systemic therapy-related hospitalizations, using nationally representative data. National Inpatient Sample data from 2005 to 2016 was used to identify systemic therapy-related complications using ICD-9 and ICD-10 external causes-of-injury codes. The primary outcome was hospitalization rates, while secondary outcomes were cost and in-hospital mortality. Overall, there were 443,222,223 hospitalizations during the study period, of which 2,419,722 were due to complications of systemic therapy. The average annual percentage change of these hospitalizations was 8.1%, compared to - 0.5% for general hospitalizations. The three most common causes for hospitalization were anemia (12.8%), neutropenia (10.8%), and sepsis (7.8%). Hospitalization rates had the highest relative increases for sepsis (1.9-fold) and acute kidney injury (1.6-fold), and the highest relative decrease for dehydration (0.21-fold) and fever of unknown origin (0.35-fold). Complications with the highest total charges were anemia ($4.6 billion), neutropenia ($3.0 billion), and sepsis ($2.5 billion). The leading causes of in-hospital mortality associated with systemic therapy were sepsis (15.8%), pneumonia (7.6%), and acute kidney injury (7.0%). Promoting initiatives such as rule OP-35, improving access to and providing coordinated care, developing systems leading to early identification and management of symptoms, and expanding urgent care access, can decrease these hospitalizations and the burden they carry on the healthcare system

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery